In this paper various approaches for face hallucination has been studied. Face hallucination transform a low resolution face image into high resolution face image by enhancing the low resolution part of the image, a low resolution image can be developed from HR image by the process of down sampling, but if a low resolution image has to convert into HR image that is not so easy process. Face hal...

Face image quality can be defined as a measure of the utility of a face image to automatic face recognition. In this work, we propose (and compare) two methods for learning face image quality based on target face quality values from (i) human assessments of face image quality (matcher-independent), and (ii) quality values computed from similarity scores (matcherdependent). A support vector regr...

The face almost always has an axis-symmetrical structure. However, as the face usually does not have an absolutely frontal pose when it is imaged, the majority of face images are not symmetrical images. These facts inspire us that the mirror image of the face image might be viewed as a representation of the face with a possible pose opposite to that of the original face image. In this paper we ...

Face image quality can be defined as a measure of the utility of a face image to automatic face recognition. In this work, we propose (and compare) two methods for automatic face image quality based on target face quality values from (i) human assessments of face image quality (matcher-independent), and (ii) quality values computed from similarity scores (matcher-dependent). A support vector re...

Face detection methods have relied on face datasets for training. However, existing face datasets tend to be in small scales for face learning in both constrained and unconstrained environments. In this paper, we first introduce our large-scale image datasets, Large-scale Labeled Face (LSLF) and noisy Large-scale Labeled Non-face (LSLNF). Our LSLF dataset consists of a large number of unconstra...

We proposed a novel method for face matching from face image database. In our method we have taken set of face images so recognition decisions need to be based on comparisons of face image database. This paper presents an approach to region based face matching. The low level image segmentation method mean shift is used to divide the image into many small regions. As a popular segmentation schem...

The paper introduces a face recognition method using probabilistic subspaces analysis on multi-module singular value features of face images. Singular value vector of a face image is valid feature for identification. But the recognition rate is low when only one module singular value vector is used for face recognition. To improve the recognition rate, many sub-images are obtained when the face...

----------------------------------------------------------------------ABSTRACT-------------------------------------------------------------------This paper presents a novel approach in face digital image searching and matching. The given key image is converted into gray scale image and after that a matrix is computed with gray scale values of the key image. Then we are collecting the diagonal k...